AI promises to go way beyond saving resource here or augmenting capability there. But how should you introduce this disruptor into your business?
The UK, which is a global centre of excellence in artificial intelligence (AI) technology, is now at a tipping point.
Sectors such as investment banking and professional services have been piloting artificial intelligence systems for some time and are starting to understand their true potential. As a result, companies are now in the process of planning implementation projects, which will see adoption levels jump dramatically over the next two years.
In fact, according to the Harvey Nash/KPMG Chief Information Officer (CIO) Survey 2017 just over a third of CIOs are either investing or planning to invest in digital labour this year. That figure leaps to two thirds among CIOs in large companies. The main drivers are improving quality (27 percent) and boosting efficiency (24 percent).
Although this market maturation is undoubtedly positive, it is also important to sound a note of caution. Vendors are currently doing a lot of overselling about the breadth and depth of AI’s potential capabilities. As a result, it is vital to keep on testing the technology to understand which promises are real and which are over-hyped.
Another important issue is that not all AI systems are the same – each is different in the way they learn and in what their strengths and weaknesses are, so it is vital to ensure you use the right technology in the right context.
Once you understand what does and does not work, bring in a technology-agnostic advisor to help you establish where the possible opportunities for AI are in the business. Ask yourself difficult questions about whether these proposed uses for AI are likely to transform your business model and, if so, what the repercussions will be.
But due to the strategic nature of the potential change, always ensure you obtain buy-in at the highest level, too. It is essential to educate the C-suite, and the management layer below, about the benefits the technology can bring and exactly what it can and cannot do, to ensure expectations will be met.
It is also worth bearing in mind also that because AI systems learn as they go, they can take time to build into becoming an effective tool. Therefore it is crucial to have a good understanding of the ways in which automation can help your business, because this will form the basis of your strategic roadmap.
But the importance of having a suitable governance structure in place should also not be underestimated. The challenge here is that most organisations’ data – data is not very clean and is subject to unconscious biases that could disadvantage some groups and damage diversity.
Another key consideration is that, once AI has been deployed effectively, it will inevitably pivot your business model. this means the company will need to undergo a corresponding internal change.
There are two ways of introducing this change: I call them ‘tinker’ and ‘transform’. And to make a success of this technology, you need to run both concurrently.
To truly pivot your business, it is almost necessary to start an arms race with competitors over how to deploy AI productively. But the issue for organisations that have been around for a while is that they tend to be risk-averse.
So I suggest creating two separate work streams. The first approach involves starting a ‘tinker’ project that aims to change the business gradually from within, by experimenting around the core.
The second method entails transforming the company by introducing disruptive projects that run in parallel to that core business. Such initiatives might involve investing in interesting start-ups or developing new products and services internally, but they contain the seeds that potentially grow into the business of the future.
The secret to success is experimenting in a controlled way, at zero risk to the business. It is not about automating things as they are now, but about trying to understand how they will look tomorrow, using transformative technology to shape your future.
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